Community-partition-based online analytical processing query optimization

In the Peer-to-Peer(P2P) environment,when the number of nodes of On-Line Analysis Processing(OLAP) query increase,network congestion will be aggravated and OLAP query efficiency will be reduced.Therefore,this paper proposed an optimized OLAP query method based on community partition.A visual community network was constructed with the method,and an algorithm of Community Partition Data-cube Search(CPDS) was designed in this structure.The results of experiment show that this algorithm can effectively avoid increasing network burden,when network OLAP nodes increase.Therefore,this method reduces congestion of network and optimizes efficiency of OLAP query,which improves the performance of decision-analysis of OLAP in P2P environment.